Head Curve Matching and Graffiti Detection

By Jing Wang, Zhijie Xu and Michael O'Grady

Abstract

Vandalism is a type of the so-called low intensity crimes. However, the nuisance and damage caused by it could cost dearly to the public to clean up. It is also technically difficult in the past to detect and prosecute such a crime, for example, graffiti making. This paper presents an automatic and live graffiti detection system using CCTV cameras and innovative vision algorithms. After a brief introduction on the problem domain, the paper proceeds to proposing a system prototype through highlighting its essential operations such as human shape and head curve recognition for triggering the follow-up operations of graffiti detection. The research methodology, the devised algorithms, and the experiment designs are then explained in details. The experiments in this programme are based on real CCTV footages recorded at a bus station. The result shows that the proposed system can detect graffiti-making actions and to locate graffiti occurring areas effectively under most live illumination conditions and is a practical solution for the design of intelligent real-time CCTV surveillance systems